The field of the disclosure relates generally to managing airspace, and more specifically, to methods and systems for tailored allocation of aircraft arrivals.
As air traffic increases worldwide, managing airspace has become more challenging, and air traffic controllers are responsible for making increasingly complex decisions. In a particularly challenging area, when an aircraft descends from cruise through an arrival phase and then onto an airport approach, several air traffic controllers are responsible for directing the aircraft through the airspace for which each individual controller is responsible and also determining a flight profile for the aircraft. While the ability of air traffic controllers to safely route aircraft has been proven by years of successful operation, the consequence of depending solely on human calculations is that the available airspace is not most efficiently used, and the aircraft cannot descend at the most optimal profile while still maintaining maximum throughput to the runways for the airports served by the arrival airspace.
The standard descent solution involves each air traffic controller giving clearance through the specific portion of the descent path which they control, from sometime prior to descent initiation all the way through to the runway. Typically, multiple airspace partitions are involved, with three or four geographically disparate air traffic control centers with their own systems, and often several different controllers within each of those centers developing and executing their own specific tactical plans for moving the flight through their airspace of responsibility, without knowledge of the subsequent controller's plan or intentions regarding the flight. This lack of an integrated airspace approach to arrivals results in a step-by-step descent characterized by several cruise and descent patterns until the aircraft reaches the runway. These relatively uncoordinated descent segments lead to increased fuel consumption, noise, emissions, and flight time.
In addition, the desire for operational economy and reduced environmental impact must be tempered with practicality from several sources. Safety must be assured by avoidance of severe weather, terrain, and other traffic and by conformance with variable airspace availability. In addition, airport and runway capacity must be maintained by precise, predictable sequencing and by coordination of arrival and departure streams. Furthermore, the optimal trajectory for each aircraft depends on its individual performance characteristics.
Each airline implements a cost index which they use to execute flight planning. The cost index is a relation between the cost of time (crew, maintenance, ownership, etc) versus the cost of fuel, taking into account the specific performance characteristics of the aircraft, the engines it is using, and the weight it has for this specific flight. The cost index varies by airline, and even by flight for a given airline, further complicating the problem of calculating a tailored arrival allocation for a specific flight. For example, one airline may prefer to land quickly and take off quickly to minimize time on the ground because the turn around time is the most important aspect of their business model. As a result, a flight for that airline may be more interested in descending with engines at higher throttle, while another airline would be more interested in fuel savings, so they would prefer descending with engines near idle.
The existing descent solution for aircraft is determined by each air traffic controller. Using the knowledge gained through many years of experience, air traffic controllers are able to manually calculate the lateral path, vertical path, and velocity appropriate for an aircraft to meet the four-dimensional position (latitude, longitude, altitude, and time) over one or more metering fixes within the descent. However, this path calculation is done in a piece-meal fashion, with each controller adjusting the flight tactically within his/her own airspace without knowledge of the next controllers execution plan.
While not currently existing, some automation tools are under development which may provide partial solutions to the problem. At least one developmental tool mirrors current air traffic practices by working in a piece-meal, segregated fashion, solving the problems in only one part of the airspace, and not coordinating these solutions with either preceding or succeeding airspaces along the route of the aircraft's flight.
The disadvantage of several controllers manually determining the appropriate flight path for an aircraft, within only the airspace for which they are responsible, is that they rely heavily on human calculations for precision calculations. Human calculations are inherently less precise than that of modern automation systems, resulting in inefficiencies. In addition, the lack of a coordinated plan stretching across multiple airspace segments leaves on-board aircraft automation entirely unable to participate in calculating and executing a most optimum path for a given descent.
Solutions such as en-route descent advisor (EDA) do not include aircraft operator preferences, inter-ATS facility coordination, and direct coordination with the aircraft operator. Instead, these solutions only provide incremental improvement to today's voice only, manual solution, and are designed with the fundamental limitations inherent in current operations.
As described above, current solutions focus on air traffic control giving aircraft discrete instructions, relayed via voice radio links between pilot and controller to turn left, right, climb, descend, or to change speed in order to get individual aircraft from departure to destination in non-integrated and largely uncoordinated steps. Such a process completely removes automation associated with the aircraft from being brought to bear in providing the most efficient solution to a flight problem. However, solving flight problems is exactly what certain aircraft systems, for example, navigation and flight management systems, have been designed to do.
In short, the airborne automation that has been developed with the express intention of optimizing flight path is completely removed from the equation, leaving only human calculations to rapidly piece together a solution. This situation is exacerbated by not only one human trying to optimize a path, but five to ten humans trying to optimize the solution, each acting independently and without knowledge of the intentions or objectives of the others.